1. Field of the Invention
The present invention considers a method for active noise cancellation using independent component analysis. More particularly, the present invention relates to a method which is operable the independent component analysis technique to an adaptive algorithm that can consider secondary or more higher statistical characteristics.
2. Description of the Related Art
FIG. 1 shows a structure of a general active noise cancellation system. In FIG. 1, a signal source(10) s is transmitted to a sensor through a channel, and a noise source(20) n0 is input in the sensor so that the combined signal and noise s+n0 form primary input(30) in the noise cancellation system.
The secondary sensor receives noise n1 through another channel, and the sensor forms reference input(40) in the noise cancellation system. The noise n1 is filtered to produce an output z, which is as close as possible of n0, by passing through an adaptive filter(50), and the primary input s+n0 deducts output z through an adder(60) and forms system output(70) u=s+n0−z in the noise cancellation system.
The purpose of the conventional active noise cancellation is to get output u=s+n0−z which is as close as possible of signal s in the point of least squares. To reach the purpose, the filter is adapted using a least mean square(LMS) adaptive algorithm to minimize the entire output of the noise cancellation system. In other words, the output in the active noise cancellation system is operated as an error signal during adaptation.
The coefficient adaptation of the filter follows the Widrow-Hoff LMS algorithm and can be expressed as following expression.Δw(k)αu(t)n1(t−k)  [Expression 1]
Where, w(k) is kth order coefficient, and t is sample index.